• Parasites, Hosts and Diseases
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• v.49 no.1
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• pp.33-38
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• 2011

Prompt and accurate diagnosis of malaria is the key to prevent disease morbidity and mortality. This study was carried out to evaluate diagnostic performance of 3 commercial rapid detection tests (RDTs), i.e., Malaria Antigen Pf/Pan$^{TM}$, Malaria Ag-Pf$^{TM}$, and Malaria Ag-Pv$^{TM}$ tests, in comparison with the microscopic and PCR methods. A total of 460 blood samples microscopically positive for Plasmodium falciparum (211 samples), P. vivax (218), mixed with P. falciparum and P. vivax (30), or P. ovale (1), and 124 samples of healthy subjects or patients with other fever-related infections, were collected. The sensitivities of Malaria Ag-Pf$^{TM}$ and Malaria Antigen Pf/Pan$^{TM}$ compared with the microscopic method for P. falciparum or P. vivax detection were 97.6% and 99.0%, or 98.6% and 99.0%, respectively. The specificities of Malaria Ag-Pf$^{TM}$, Malaria Ag-Pv$^{TM}$, and Malaria Antigen Pf/Pan$^{TM}$ were 93.3%,98.8%, and 94.4%, respectively. The sensitivities of Malaria Ag-Pf$^{TM}$, Malaria Antigen Pf/Pan$^{TM}$, and microscopic method, when PCR was used as a reference method for P. falciparum or P. vivax detection were 91.8%, 100%, and 96.7%, or 91.9%,92.6%, and 97.3%, respectively. The specificities of Malaria Ag-Pf$^{TM}$, Malaria Ag-Pv$^{TM}$, Malaria Antigen Pf/Pan$^{TM}$, and microscopic method were 66.2%, 92.7%, 73.9%, and 78.2%, respectively. Results indicated that the diagnostic performances of all the commercial RDTs are satisfactory for application to malaria diagnosis.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.4 s.107
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• pp.341-350
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• 2006

In this paper, a new method for detecting breast cancer is proposed, which utilizes dielectric characteristics of pathological tissues and time delay of back scattered response, and its feasibility was investigated. We have developed a detection algorithm and verified it by numerical simulation and measurement for a prototype system. For a prototype system, we have fabricated experimental model(artificial breast with a cancer) and UWB(ultra-wideband) antenna. The results of the measurement simulation show an excellent detection capability of a cancer tissue. It is found that a good UWB antenna and a good calibration signal are key elements of such detection system. Further study is ongoing to develop a commercial system.

• Smart Structures and Systems
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• v.17 no.6
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• pp.957-980
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• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Structural Engineering and Mechanics
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• v.36 no.5
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• pp.643-667
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• 2010

The classical flexibility difference method detects damage by observing the difference of conventional deflection flexibility matrices between pre- and post-damaged states of a structure. This method is not able to identify multiple damage scenarios, and its criteria to identify damage depend upon the boundary conditions of structures. The key point behind the inability and dependence is revealed in this study. A more feasible flexibility for damage detection, the Angle-between-String-and-Horizon (ASH) flexibility, is proposed. The physical meaning of the new flexibility is given, and synthesis of the new flexibility matrix by modal frequencies and translational mode shapes is formulated. The damage indicators are extracted from the difference of ASH flexibility matrices between the pre- and post-damaged structures. One feature of the ASH flexibility is that the components in the ASH flexibility matrix are associated with elements instead of Nodes or DOFs. Therefore, the damage indicators based on the ASH flexibility are mapped to structural elements directly, and thus they can pinpoint the damaged elements, which is appealing to damage detection for complex structures. In addition, the change in the ASH flexibility caused by damage is not affected by boundary conditions, which simplifies the criteria to identify damage. Moreover, the proposed method can determine relatively the damage severity. Because the proposed damage indicator of an element mainly reflects the deflection change within the element itself, which significantly reduces the influence of the damage in one element on the damage indicators of other damaged elements, the proposed method can identify multiple damage locations. The viability of the proposed approach has been demonstrated by numerical examples and experimental tests on a cantilever beam and a simply supported beam.

• Korean Journal of Clinical Laboratory Science
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• v.44 no.2
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• pp.81-85
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• 2012

This study was undertaken to evaluate phenotypic and genotypic methods for detection of Metallo-Beta-Lactamases (MBLs) among nosocomial Pseudomonas aeruginosa. Of the 50 P. aeruginosa isolates from clinical specimens, 20 were evaluated for carbapenem resistance and screened for MBL by double-disk synergy test and combined-disk test. Nineteen strains (95%) were found to be MBL producers among the 20 P. aeruginosa. MBL positives were further confirmed by Polymerase Chain Reaction (PCR). For the IMP and VIM types of MBLs, PCR analysis was performed on 19 of the 20, and 10 were positive for VIM MBL type. This study reports the validation of a simple and accurate MBL detection method that can be easily incorporated into the daily routine of a clinical laboratory. Early detection of MBL-carrying organisms, including those with susceptibility to carbapenems, is of paramount clinical importance, as it allows rapid initiation of strict infection control practices as well as therapeutic guidance for confirmed infection.Key Words : Hepatitis A virus (HAV), Anti-HAV, Hospital workers, Prevalence, Vaccination

• Korean Journal of Veterinary Service
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• v.44 no.3
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• pp.163-168
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• 2021

The rapid and reliable detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a key role in isolating infected patients and preventing further viral transmission. In this study, we evaluated the clinical diagnostic performances of a commercial real-time reverse transcription loop-mediated isothermal amplification (RRT-LAMP) assay (Isopollo^® COVID-2 assay, M-monitor, Daegu, Korea) using eighty COVID-19 suspected clinical samples and compared these with the results of a commercial real-time reverse transcription polymerase chain reaction (RT-qPCR) assay (Allplex^TM 2019-nCoV rRT-QPCR Assay, SeeGene, Seoul, Korea). The results of the RRT-LAMP assay targeting the N or RdRp gene of SARS-CoV-2 showed perfect agreement with the RT-qPCR assay results in terms of detection. Furthermore, the RRT-LAMP assay was completed in just within a 20-min reaction time, which is significantly faster than about the 2 h currently required for the RT-qPCR assay, thus enabling prompt decision making regarding the isolation of infected patients. The RRT-LAMP assay will be a valuable tool for rapid, sensitive, and specific detection of SARS-CoV-2 in human or unexpected animal clinical cases.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.65-75
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• 2009

The development of IT technology, Internet popularity is increasing geometrically. However, as its side effect, the intrusion behaviors such as information leakage for key system and infringement of computation network etc are also increasing fast. The attack traffic detection method which is suggested in this study utilizes the Snort, traditional NIDS, filters the packet with false positive among the detected attack traffics using Nmap information. Then, it performs the secondary filtering using nessus vulnerability information and finally performs correlation analysis considering appropriateness of management system, severity of signature and security hole so that it could reduce false positive alarm message as well as minimize the errors from false positive and as a result, it raised the overall attack detection results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1720-1728
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• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.1-14
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• 2024

Global navigation satellite system (GNSS) providing position, navigation and timing (PNT) services consist of satellite, ground, and user systems. Monitoring stations, a key element of the ground segment, play a crucial role in continuously collecting satellite navigation signals for service provision and fault detection. These stations detect anomalies such as threats to the signal-in-space (SIS) of satellites, receiver issues, and local threats. They deliver received data and detection results to the master station. This paper introduces the main monitoring algorithms and measurement pre-processing processes for quality assessment and fault detection of received satellite signals in current satellite navigation system monitoring stations. Furthermore, it proposes a strategy for the development of components, architecture, and algorithms for the new regional navigation satellite system (RNSS) monitoring stations.